The Dental Neglect Scale in adolescents

<p>Abstract</p> <p>Background</p> <p>Dental neglect has been found to be related to poor oral health, a tendency not to have had routine check-ups, and a longer period of time since the last dental appointment in samples of children and adults. The Dental Neglect Scale (DNS) has been found to be a valid measure of dental neglect in samples of children and adults, and may be valid for adolescents as well. We administered the DNS to a sample of adolescents and report on the relationships between the DNS and oral health status, whether or not the adolescent has been to the dentist recently for routine check-ups, and whether or not the adolescent currently goes to a dentist. We also report the internal and test-retest reliabilities of the DNS in this sample, as well as the results of an exploratory factor analysis.</p> <p>Methods</p> <p>One hundred seventeen adolescents from seven youth groups in the Seattle-Tacoma metropolitan area (Washington State, U.S.) completed the DNS and indicated whether they currently go to a dentist, while parents indicated whether the adolescent had a check-up in the previous three years. Adolescents also received a dental screening. Sixty six adolescents completed the questionnaire twice. T-tests were used to compare DNS scores of adolescents who have visible caries or not, adolescents who have had a check-up in the past three years or not, and adolescents who currently go to a dentist or not. Internal reliability was measured by Cronbach's alpha, and test-rest reliability was measured by intra-class correlation. Factor analysis (Varimax rotation) was used to examine the factor structure.</p> <p>Results</p> <p>In each comparison, significantly higher DNS scores were observed in adolescents with visible caries, who have not had a check-up in the past three years, or who do not go to a dentist (all p values < 0.05). The test-retest reliability of the DNS was high (ICC = 0.81), and its internal reliability was acceptable (Cronbach's alpha = 0.60). Factor analysis yielded two factors, characterized by home care and visiting a dentist.</p> <p>Conclusion</p> <p>The DNS appears to operate similarly in this sample of adolescents as it has in other samples of children and adults.</p

Tropical carbon sink accelerated by symbiotic dinitrogen fixation

A major uncertainty in the land carbon cycle is whether symbiotic nitrogen fixation acts to enhance the tropical forest carbon sink. Nitrogen-fixing trees can supply vital quantities of the growth-limiting nutrient nitrogen, but the extent to which the resulting carbon–nitrogen feedback safeguards ecosystem carbon sequestration remains unclear. We combine (i) field observations from 112 plots spanning 300 years of succession in Panamanian tropical forests, and (ii) a new model that resolves nitrogen and light competition at the scale of individual trees. Fixation doubled carbon accumulation in early succession and enhanced total carbon in mature forests by ~10% (~12MgC ha−1) through two mechanisms: (i) a direct fixation effect on tree growth, and (ii) an indirect effect on the successional sequence of non-fixing trees. We estimate that including nitrogen-fixing trees in Neotropical reforestation projects could safeguard the sequestration of 6.7 Gt CO2 over the next 20 years. Our results highlight the connection between functional diversity of plant communities and the critical ecosystem service of carbon sequestration for mitigating climate change

The vicious cycle of dental fear: exploring the interplay between oral health, service utilization and dental fear

BACKGROUND: Based on the hypothesis that a vicious cycle of dental fear exists, whereby the consequences of fear tend to maintain that fear, the relationship between dental fear, self-reported oral health status and the use of dental services was explored. METHODS: The study used a telephone interview survey with interviews predominantly conducted in 2002. A random sample of 6,112 Australian residents aged 16 years and over was selected from 13 strata across all States and Territories. Data were weighted across strata and by age and sex to obtain unbiased population estimates. RESULTS: People with higher dental fear visited the dentist less often and indicated a longer expected time before visiting a dentist in the future. Higher dental fear was associated with greater perceived need for dental treatment, increased social impact of oral ill-health and worse self-rated oral health. Visiting patterns associated with higher dental fear were more likely to be symptom driven with dental visits more likely to be for a problem or for the relief of pain. All the relationships assumed by a vicious cycle of dental fear were significant. In all, 29.2% of people who were very afraid of going to the dentist had delayed dental visiting, poor oral health and symptom-driven treatment seeking compared to 11.6% of people with no dental fear. CONCLUSION: Results are consistent with a hypothesised vicious cycle of dental fear whereby people with high dental fear are more likely to delay treatment, leading to more extensive dental problems and symptomatic visiting patterns which feed back into the maintenance or exacerbation of existing dental fear

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

The impact of carotid plaque presence and morphology on mortality outcome in cardiological patients

BACKGROUND: Carotid plaque severity and morphology can affect cardiovascular prognosis. We evaluate both the importance of echographically assessed carotid artery plaque geometry and morphology as predictors of death in hospitalised cardiological patients. METHODS: 541 hospitalised patients admitted in a cardiological division (age = 66 ± 11 years, 411 men), have been studied through ultrasound Duplex carotid scan and successively followed-up for a median of 34 months. Echo evaluation assessed plaque severity and morphology (presence of heterogeneity and profile). RESULTS: 361 patients showed carotid stenosis (67% with <50% stenosis, 18% with 50–69% stenosis, 9% with >70% stenosis, 4% with near occlusion and 2% with total occlusion). During the follow-up period, there were 83 all-cause deaths (15% of the total population). Using Cox's proportional hazard model, age (RR 1.06, 95% CI 1.03–1.09, p = 0.000), ejection fraction > 50% (RR = 0.62, 95% CI 0.4–0.96, p = 0.03), treatment with statins (RR = 0.52, 95% CI 0.29–0.95, p = 0.34) and the presence of a heterogeneous plaque (RR 1.6; 95% CI, 1.2 to 2.14, p = 0.002) were independent predictors of death. Kaplan – Meier survival estimates have shown the best outcome in patients without plaque, intermediate in patients with homogeneous plaques and the worst outcome in patients with heterogeneous plaques (90% vs 79% vs 73%, p = 0.0001). CONCLUSION: In hospitalised cardiological patients, carotid plaque presence and morphology assessed by ultrasound are independent predictors of death

The role of low-volatility organic compounds in initial particle growth in the atmosphere

About half of present-day cloud condensation nuclei originate from atmospheric nucleation, frequently appearing as a burst of new particles near midday1. Atmospheric observations show that the growth rate of new particles often accelerates when the diameter of the particles is between one and ten nanometres2, 3. In this critical size range, new particles are most likely to be lost by coagulation with pre-existing particles4, thereby failing to form new cloud condensation nuclei that are typically 50 to 100 nanometres across. Sulfuric acid vapour is often involved in nucleation but is too scarce to explain most subsequent growth5, 6, leaving organic vapours as the most plausible alternative, at least in the planetary boundary layer7, 8, 9, 10. Although recent studies11, 12, 13 predict that low-volatility organic vapours contribute during initial growth, direct evidence has been lacking. The accelerating growth may result from increased photolytic production of condensable organic species in the afternoon2, and the presence of a possible Kelvin (curvature) effect, which inhibits organic vapour condensation on the smallest particles (the nano-Köhler theory)2, 14, has so far remained ambiguous. Here we present experiments performed in a large chamber under atmospheric conditions that investigate the role of organic vapours in the initial growth of nucleated organic particles in the absence of inorganic acids and bases such as sulfuric acid or ammonia and amines, respectively. Using data from the same set of experiments, it has been shown15 that organic vapours alone can drive nucleation. We focus on the growth of nucleated particles and find that the organic vapours that drive initial growth have extremely low volatilities (saturation concentration less than 10−4.5 micrograms per cubic metre). As the particles increase in size and the Kelvin barrier falls, subsequent growth is primarily due to more abundant organic vapours of slightly higher volatility (saturation concentrations of 10−4.5 to 10−0.5 micrograms per cubic metre). We present a particle growth model that quantitatively reproduces our measurements. Furthermore, we implement a parameterization of the first steps of growth in a global aerosol model and find that concentrations of atmospheric cloud concentration nuclei can change substantially in response, that is, by up to 50 per cent in comparison with previously assumed growth rate parameterizations

Visualization and Curve-Parameter Estimation Strategies for Efficient Exploration of Phenotype Microarray Kinetics

The Phenotype MicroArray (OmniLog® PM) system is able to simultaneously capture a large number of phenotypes by recording an organism's respiration over time on distinct substrates. This technique targets the object of natural selection itself, the phenotype, whereas previously addressed '-omics' techniques merely study components that finally contribute to it. The recording of respiration over time, however, adds a longitudinal dimension to the data. To optimally exploit this information, it must be extracted from the shapes of the recorded curves and displayed in analogy to conventional growth curves.The free software environment R was explored for both visualizing and fitting of PM respiration curves. Approaches using either a model fit (and commonly applied growth models) or a smoothing spline were evaluated. Their reliability in inferring curve parameters and confidence intervals was compared to the native OmniLog® PM analysis software. We consider the post-processing of the estimated parameters, the optimal classification of curve shapes and the detection of significant differences between them, as well as practically relevant questions such as detecting the impact of cultivation times and the minimum required number of experimental repeats.We provide a comprehensive framework for data visualization and parameter estimation according to user choices. A flexible graphical representation strategy for displaying the results is proposed, including 95% confidence intervals for the estimated parameters. The spline approach is less prone to irregular curve shapes than fitting any of the considered models or using the native PM software for calculating both point estimates and confidence intervals. These can serve as a starting point for the automated post-processing of PM data, providing much more information than the strict dichotomization into positive and negative reactions. Our results form the basis for a freely available R package for the analysis of PM data

A Systems Model for Immune Cell Interactions Unravels the Mechanism of Inflammation in Human Skin

Inflammation is characterized by altered cytokine levels produced by cell populations in a highly interdependent manner. To elucidate the mechanism of an inflammatory reaction, we have developed a mathematical model for immune cell interactions via the specific, dose-dependent cytokine production rates of cell populations. The model describes the criteria required for normal and pathological immune system responses and suggests that alterations in the cytokine production rates can lead to various stable levels which manifest themselves in different disease phenotypes. The model predicts that pairs of interacting immune cell populations can maintain homeostatic and elevated extracellular cytokine concentration levels, enabling them to operate as an immune system switch. The concept described here is developed in the context of psoriasis, an immune-mediated disease, but it can also offer mechanistic insights into other inflammatory pathologies as it explains how interactions between immune cell populations can lead to disease phenotypes

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives